2000DINESHBHANUKA/smart-home-llama3

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kTool Calling:SupportedPublished:Jun 9, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The 2000DINESHBHANUKA/smart-home-llama3 is an 8 billion parameter Llama 3-based instruction-tuned causal language model, finetuned by 2000DINESHBHANUKA. It was optimized for training speed using Unsloth and Huggingface's TRL library, building upon the unsloth/llama-3-8b-Instruct-bnb-4bit model. This model is designed for general language understanding and generation tasks, leveraging the Llama 3 architecture for efficient performance.

Loading preview...

Model Overview

The 2000DINESHBHANUKA/smart-home-llama3 is an 8 billion parameter instruction-tuned language model, developed by 2000DINESHBHANUKA. It is based on the Llama 3 architecture, specifically finetuned from the unsloth/llama-3-8b-Instruct-bnb-4bit model.

Key Characteristics

  • Architecture: Llama 3-based, 8 billion parameters.
  • Finetuning: Utilizes Unsloth and Huggingface's TRL library for accelerated training.
  • Origin: Finetuned from unsloth/llama-3-8b-Instruct-bnb-4bit.
  • License: Distributed under the Apache-2.0 license.

Training Optimization

A notable aspect of this model is its training methodology, which leveraged Unsloth to achieve a 2x speedup during the finetuning process. This optimization makes it efficient for developers looking to deploy Llama 3-based models with faster iteration cycles.

Potential Use Cases

This model is suitable for a range of general-purpose natural language processing tasks, including but not limited to:

  • Instruction following
  • Text generation
  • Question answering
  • Conversational AI applications

Finetunes
1 models